Mathieu Bonneau

Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement

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Laurianne Canario

Génétique Physiologie et Systèmes d'Elevage

Régis Sabbadin

Mathématiques et Informatique Appliquées

Nathalie Peyrard

Mathématiques et Informatique Appliquées

Julien Martin

Centre d’Etudes et de Recherches de Sciences Administratives et Politiques

Fred A. Johnson

University of Florida

Rémy Arquet

Institut Pasteur de la Guadeloupe

Jean‐Stéphane Bailly

AgroParisTech

Christina M. Romagosa

University of Florida

Jehan-Antoine Vayssade

Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement

Océane Girardie

Génétique Physiologie et Systèmes d'Elevage

Cooperative Institutions

Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement

Institut National de la Recherche Agronomique

Université de Toulouse

Unité de Recherche Agrosystèmes tropicaux

Agroécologie

Département Génétique Animale

Génétique Physiologie et Systèmes d'Elevage

United States Geological Survey

Institut National de la Recherche Agronomique du Niger

Centre National de la Recherche Scientifique

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Reciprocal translocations in pigs

Journal of Heredity (1984)

C.P. Popescu Mathieu Bonneau Michèle Tixier I. Bahri Jeannine Boscher

In France, the national computerized program for sow herd management regularly delivers a listing of hypoprolific boars for which a cytogenetic evaluation is required, and participates in the differential diagnosis of the other causes of reduced prolificacy. Two reciprocal translocations, 4/14 and 7/15, reducing the prolificacy by about 45 percent have been discovered since 1979. A third one, leading to a prolificacy reduction of about 28 percent, is described in the present paper. The effects of translocation 4/14 were studied in an experimental herd, in which the ovulation rate did not seem to be modified and the early embryonic mortality accounted for the decrease in litter size. The growth rate at day 35 was higher in piglets carrying the chromosomal abnormality than in their normal littermates, i.e., 215 vs. 182 g per day (P less than 0.10). The economic consequences of using a boar carrying a translocation on a group of 21 sows were estimated by means of a simulation model "Porsim." When prolificacy decreased by five piglets per litter, the losses represented 157 piglets, i.e., about $4000. If, in addition to this, the percentage of non-returns into heat decreased by 35 percent, the losses then represented 248 piglets, i.e., $6000. Because of this important economic risk, it is suggested that measures be taken to detect defective animals and to prevent their use.

Litter

BOAR

10.1093/oxfordjournals.jhered.a109983

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Citations (37)

Using structured decision making and category count models to develop optimal policies for imperiled salamander habitat restoration

HAL (Le Centre pour la Communication Scientifique Directe) (2016)

Katie O'Donnell A. Johnson Mathieu Bonneau Julien Martin Paul L. Fackler

Frosted flatwoods salamanders, Ambystoma cingulatum, are federally-listed pond-breeding salamanders that inhabit wetlands embedded in pine-wiregrass ecosystems. They have likely declined due to widespread destruction of longleaf pine ecosystems and habitat degradation due to fire suppression. To explicitly address the uncertainty regarding necessary management actions for flatwoods salamander recovery, we held a structured decision making (SDM) workshop to develop an adaptive management framework for habitat restoration at one of the last strongholds for A. cingulatum-- St. Marks National Wildlife Refuge. We identified the need for state-dependent decisions, and defined possible states as combinations of habitat suitability (unsuitable (U) or suitable (S)) and occupancy (occupied (O) or unoccupied (U)), resulting in 4 combinations (S/O, S/U, U/O, U/U). We defined potential management actions for each state, and used expert elicitation to generate transition probabilities between states under two management portfolios: (A) a “future status quo” of frequent growing season burns, and (B) additional actions such as head-starting and fine-scale restoration. We then used a stochastic dynamic programming approach known as a category count model to develop a preliminary optimal management policy.

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Integrating encounter theory with decision analysis to evaluate collision risk and determine optimal protection zones for wildlife

Journal of Applied Ecology (2018)

Bradley J. Udell Julien Martin Robert J. Fletcher Mathieu Bonneau Holly H. Edwards

Abstract Better understanding human–wildlife interactions and their links with management can help improve the design of wildlife protection zones. One example is the problem of wildlife collisions with vehicles or human‐built structures (e.g., power lines, wind farms). In fact, collisions between marine wildlife and watercraft are among the major threats faced by several endangered species of marine mammals. Natural resource managers are therefore interested in finding cost‐effective solutions to mitigate these threats. We combined abundance estimators with encounter rate theory to estimate relative lethal collision risk of the Florida manatee ( Trichechus manatus latirostris ) from watercraft. We first modelled seasonal abundance of watercraft and manatees using a Bayesian analysis of aerial survey count data. We then modelled relative lethal collision risk in space and across seasons. Finally, we applied decision analysis and Linear Integer Programming to determine the optimal design of speed zones in terms of relative risk to manatees and costs to waterway users. We used a Pareto efficient frontier approach to evaluate the performance of alternative zones, which included additional practical considerations (e.g., spatial aggregation of speed zones) in relation to the optimal zone configurations. Under the various relationships for probability of death given strike speed that we considered, the current speed zones reduced the relative lethal collision risk by an average of 51.5% to 70.0% compared to the scenario in which all speed regulations were removed (i.e., the no‐protection scenario). We identified optimal zones and near‐optimal zones with additional management considerations that improved upon the current zones in terms of cost or relative risk. Policy implications . Our analytical framework combines encounter rate theory and decision analysis to quantify the effectiveness of speed zones in protecting manatees while accounting for uncertainty. Our approach can be used to optimize the design of protection zones intended to reduce conflicts between human waterborne activity and marine mammals. This framework could be extended to address many other problems of human–wildlife interactions, such as the optimal placement of wind farms to minimize collisions with wildlife or the optimal allocation of ranger effort to mitigate poaching threats.

Watercraft

Manatee

10.1111/1365-2664.13290

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Citations (20)

Category count models for adaptive management of metapopulations: Case study of an imperiled salamander

Conservation Science and Practice (2020)

Katherine M. O’Donnell Paul L. Fackler Fred A. Johnson Mathieu Bonneau Julien Martin

Abstract Managing spatially structured populations of imperiled species presents many challenges. Spatial structure can make it difficult to predict population responses to potential recovery activities, and learning through experimentation may not be advised if it could harm threatened populations. Adaptive management provides an appealing framework when experimentation is considered too risky or time consuming; we used such an approach for imperiled flatwoods salamanders at a Florida wildlife refuge. We represented this metapopulation with category count models and used stochastic dynamic programming to identify optimal decision policies that weighed trade‐offs between metapopulation persistence and management costs. We defined possible wetland categories in terms of habitat suitability and occupancy, specified category‐specific management actions, and identified transition probabilities via expert elicitation for two management strategies: “future” status quo (FSQ; frequent growing‐season burns) and extra management actions (EMA; restoration, translocation, head‐starting). We simulated metapopulation dynamics using the resulting optimal management policy and found that under model FSQ, occupancy steadily declined over time, indicating that populations would rapidly become extirpated; with model EMA, occupancy remained stable, suggesting that populations would persist only if additional actions are applied and are effective. This approach can be used to identify optimal solutions while accounting for uncertainty and considering both habitat and population dynamics, and to help managers make conservation decisions for populations at imminent risk of extinction.

Metapopulation

Occupancy

Adaptive Management

Extinction (optical mineralogy)

10.1111/csp2.180

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Citations (3)

Reinforcement-learning for sampling design in Markov random fields

HAL (Le Centre pour la Communication Scientifique Directe) (2012)

Mathieu Bonneau Nathalie Peyrard Régis Sabbadin

Optimal sampling in spatial random fields is a complex problem, which mobilizes several research fields in spatial statistics and artificial intelligence. We consider the case where observations are discrete-valued and modelled by a Markov Random Field. Then we encode the sampling problem into the Markov Decision Process (MDP) framework. After exploring existing heuristic solutions as well as classical algorithms from the field of Reinforcement Learning (RL), we design an original algorithm, LSDP (Least Square Dynamic Programming), which uses simulated trajectories to solve approximately any finite-horizon MDP problem. Based on an empirical study of the behaviour of these different approaches on binary models, we derive the following conclusions: i) a naive heuristic, consisting in sampling sites where marginals are the most uncertain, is already an efficient sampling approach. ii) LSDP outperforms all the classical RL approaches we have tested. iii) LSDP outperforms the heuristic in cases when reconstruction errors have a high cost, or sampling actions are constrained. In addition, LSDP readily handles action costs in the optimisation problem, as well as cases when some sites of the MRF can not be observed.

Markov random field

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An adaptive sampling method using Hidden Markov Random Fields for the mapping of weed at the field scale

HAL (Le Centre pour la Communication Scientifique Directe) (2011)

Mathieu Bonneau Sabrina Gaba Nathalie Peyrard Régis Sabbadin

Adaptive sampling

Markov random field

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[Two novel reciprocal translocations involving chromosome 6 in the domestic pig].

PubMed (1991)

Mathieu Bonneau Jeannine Boscher Delate Jj C. LEGAULT Popescu Cp

BOAR

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Domestic pig

Large white

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The use of artificial intelligence techniques for detection and identification in the animal sector

HAL (Le Centre pour la Communication Scientifique Directe) (2020)

Bernard Benet Anders Mårell Yves Boscardin Mathieu Bonneau Laurianne Canario

Identification

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Dynamic minimum set problem for reserve design: Heuristic solutions for large problems

PLoS ONE (2018)

Mathieu Bonneau Régis Sabbadin Fred A. Johnson Bradley M. Stith

Conversion of wild habitats to human dominated landscape is a major cause of biodiversity loss. An approach to mitigate the impact of habitat loss consists of designating reserves where habitat is preserved and managed. Determining the most valuable areas to preserve in a landscape is called the reserve design problem. There exists several possible formulations of the reserve design problem, depending on the objectives and the constraints. In this article, we considered the dynamic problem of designing a reserve that contains a desired area of several key habitats. The dynamic case implies that the reserve cannot be designed in one time step, due to budget constraints, and that habitats can be lost before they are reserved, due for example to climate change or human development. We proposed two heuristics strategies that can be used to select sites to reserve each year for large reserve design problem. The first heuristic is a combination of the Marxan and site-ordering algorithms and the second heuristic is an augmented version of the common naive myopic heuristic. We evaluated the strategies on several simulated examples and showed that the augmented greedy heuristic is particularly interesting when some of the habitats to protect are particularly threatened and/or the compactness of the network is accounted for.

Heuristics

10.1371/journal.pone.0193093

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Citations (3)

Decision analysis for optimal control of invasive species in the Everglades

HAL (Le Centre pour la Communication Scientifique Directe) (2016)

Fred A. Johnson Mathieu Bonneau Julien Martin Christina M. Romagosa Paul L. Fackler

Invasive species management has emerged as a high-priority issue in planning the restoration and conservation of the Greater Everglades. Management agencies are currently involved in a number of management activities such as coordination of operational control efforts and monitoring of many invasive species. Given the limited amount of resources to control invasive species and their potential to impose great damage to ecological systems and ecosystems services, it is important to maximize efficiency of control and monitoring efforts. Decision theory provides a framework for improving the efficiency of the control of invasive species. We focus on the application of decision theory to two case studies in the Greater Everglades: 1) Tegus (Tupinambis spp.) are lizards native to South America that have become established in Florida. The focus is on containing the population to prevent expansion into Everglades National Park. In August 2015 we met with state and federal members of the research and management communities to identify management objectives, potential control actions, and information needed to control the spread of tegus in Florida. We developed a matrix population model for tegus, and a spatial optimization algorithm to help inform control, monitoring, and research efforts. 2) Control of the invasive melaleuca (Melaleuca quinquenervia) in the Everglades has met some success, but managers are interested in more cost-effective control. We considered the application of optimization methods to identify the most cost-effective application of treatments.

Adaptive Management

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